Data Completeness
9/27 Core Data 34 Datasets 14 Organisations Show legend
What is Data Completeness?
Data Completeness defines a set of core data that are essential for preparedness and emergency response. For select countries, the HDX Team and trusted partners evaluate datasets available on HDX and add those meeting the definition of a core data category to the Data Completeness board above. Please help us improve this feature by sending your feedback to hdx@un.org.
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  • Dataset partially matches criteria and/or is not up-to-date
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Affected People
9 Datasets
Internally-Displaced Persons
International Organization for Migration
Returnees
International Organization for Migration
Humanitarian Profile Locations
International Organization for Migration
UN Operational Satellite Applications Programme (UNOSAT)
UN Operational Satellite Applications Programme (UNOSAT)
UN Operational Satellite Applications Programme (UNOSAT)
Humanitarian Needs
Casualties
Armed Conflict Location & Event Data Project (ACLED)
Coordination & Context
10 Datasets
3w - Who is doing what where
International Aid Transparency Initiative
Conflict Events
Armed Conflict Location & Event Data Project (ACLED)
Transportation Status
WFP - World Food Programme
WFP - World Food Programme
Damaged & Destroyed Buildings
Food Security & Nutrition
3 Datasets
Global Acute Malnutrition Rate
Severe Acute Malnutrition Rate
Food Prices
WFP - World Food Programme
Geography & Infrastructure
9 Datasets
Administrative Divisions
Populated Places
Humanitarian OpenStreetMap Team (HOT)
Roads
Humanitarian OpenStreetMap Team (HOT)
WFP - World Food Programme
WFP - World Food Programme
OCHA Sudan
Airports
Health & Education
5 Datasets
Health Facilities
Global Healthsites Mapping Project
Humanitarian OpenStreetMap Team (HOT)
Affected Schools
Population & Socio-economy
3 Datasets
Baseline Population by Age & Sex
Poverty Rate
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  • Updated March 30, 2020 | Dataset date: Feb 20, 2020
    This dataset updates: Every year
    Camps in Sudan for IDP - IOM
  • Updated March 30, 2020 | Dataset date: Feb 20, 2020
    This dataset updates: Every year
    IOM through DTM registration of IDPs in Sudan
  • Updated March 30, 2020 | Dataset date: Mar 30, 2020
    This dataset updates: Every year
    Sudan IDP Settlements by Risk level data by locality and state wise.
  • 4800+ Downloads
    Updated March 30, 2020 | Dataset date: Mar 30, 2020
    This dataset updates: Every day
    FTS publishes data on humanitarian funding flows as reported by donors and recipient organizations. It presents all humanitarian funding to a country and funding that is specifically reported or that can be specifically mapped against funding requirements stated in humanitarian response plans. The data comes from OCHA's Financial Tracking Service, is encoded as utf-8 and the second row of the CSV contains HXL tags.
  • 100+ Downloads
    Updated March 29, 2020 | Dataset date: Jan 1, 1999-Dec 31, 2018
    This dataset updates: Every year
    FAO statistics collates and disseminates food and agricultural statistics globally. The division develops methodologies and standards for data collection, and holds regular meetings and workshops to support member countries develop statistical systems. We produce publications, working papers and statistical yearbooks that cover food security, prices, production and trade and agri-environmental statistics.
  • 6100+ Downloads
    Updated March 29, 2020 | Dataset date: Jan 1, 1990-Mar 15, 2020
    This dataset updates: Every week
    This dataset contains Global Food Prices data from the World Food Programme covering foods such as maize, rice, beans, fish, and sugar for 76 countries and some 1,500 markets. It is updated weekly but contains to a large extent monthly data. The data goes back as far as 1992 for a few countries, although many countries started reporting from 2003 or thereafter.
  • 700+ Downloads
    Updated March 29, 2020 | Dataset date: Jan 15, 2001-Jan 15, 2020
    This dataset updates: Every week
    This dataset contains Food Prices data for Sudan. Food prices data comes from the World Food Programme and covers foods such as maize, rice, beans, fish, and sugar for 76 countries and some 1,500 markets. It is updated weekly but contains to a large extent monthly data. The data goes back as far as 1992 for a few countries, although many countries started reporting from 2003 or thereafter.
  • 100+ Downloads
    Updated March 29, 2020 | Dataset date: Jan 1, 1997-Dec 31, 2020
    This dataset updates: As needed
    The ACLED project codes reported information on the type, agents, exact location, date, and other characteristics of political violence events, demonstrations and select politically relevant non-violent events. ACLED focuses on tracking a range of violent and non-violent actions by political agents, including governments, rebels, militias, communal groups, political parties, external actors, rioters, protesters and civilians. Data contain specific information on the date, location, group names, interaction type, event type, reported fatalities and contextual notes.
  • 100+ Downloads
    Updated March 28, 2020 | Dataset date: Jan 1, 1989-Dec 31, 2018
    This dataset updates: As needed
    This dataset is UCDP's most disaggregated dataset, covering individual events of organized violence (phenomena of lethal violence occurring at a given time and place). These events are sufficiently fine-grained to be geo-coded down to the level of individual villages, with temporal durations disaggregated to single, individual days. Sundberg, Ralph, and Erik Melander, 2013, “Introducing the UCDP Georeferenced Event Dataset”, Journal of Peace Research, vol.50, no.4, 523-532 Högbladh Stina, 2019, “UCDP GED Codebook version 19.1”, Department of Peace and Conflict Research, Uppsala University
  • 100+ Downloads
    Updated March 28, 2020 | Dataset date: Jan 1, 2008-Dec 31, 2018
    This dataset updates: As needed
    Internally displaced persons are defined according to the 1998 Guiding Principles (http://www.internal-displacement.org/publications/1998/ocha-guiding-principles-on-internal-displacement) as people or groups of people who have been forced or obliged to flee or to leave their homes or places of habitual residence, in particular as a result of armed conflict, or to avoid the effects of armed conflict, situations of generalized violence, violations of human rights, or natural or human-made disasters and who have not crossed an international border. "People Displaced" refers to the number of people living in displacement as of the end of each year. "New Displacement" refers to the number of new cases or incidents of displacement recorded, rather than the number of people displaced. This is done because people may have been displaced more than once. Contains data from IDMC's Global Internal Displacement Database.
  • 79000+ Downloads
    Updated Live | Dataset date: Jan 22, 2020-Mar 27, 2020
    This dataset updates: Live
    Novel Corona Virus (COVID-19) epidemiological data since 22 January 2020. The data is compiled by the Johns Hopkins University Center for Systems Science and Engineering (JHU CCSE) from various sources including the World Health Organization (WHO), DXY.cn. Pneumonia. 2020, BNO News, National Health Commission of the People’s Republic of China (NHC), China CDC (CCDC), Hong Kong Department of Health, Macau Government, Taiwan CDC, US CDC, Government of Canada, Australia Government Department of Health, European Centre for Disease Prevention and Control (ECDC), Ministry of Health Singapore (MOH). JSU CCSE maintains the data on the 2019 Novel Coronavirus COVID-19 (2019-nCoV) Data Repository on github. Fields available in the data include Province/State, Country/Region, Last Update, Confirmed, Suspected, Recovered, Deaths. On 23/03/2020, a new data structure was released. The current resources are: time_series_covid19_confirmed_global.csv time_series_covid19_deaths_global.csv for the latest time series data ---DEPRECATION WARNING--- The resources below ceased being updated on 22/03/2020 and were removed on 26/03/2020: time_series_19-covid-Confirmed.csv time_series_19-covid-Deaths.csv time_series_19-covid-Recovered.csv
  • 400+ Downloads
    Updated March 24, 2020 | Dataset date: Jan 1, 2012-Dec 31, 2018
    This dataset updates: As needed
    Contains data from World Health Organization's data portal covering the following categories: Mortality and global health estimates, Sustainable development goals, Millennium Development Goals (MDGs), Health systems, Malaria, Tuberculosis, Child health, Infectious diseases, World Health Statistics, Health financing, Public health and environment, Substance use and mental health, Tobacco, Injuries and violence, HIV/AIDS and other STIs, Nutrition, Urban health, Noncommunicable diseases, Noncommunicable diseases CCS, Negelected tropical diseases, Health Equity Monitor, Infrastructure, Essential health technologies, Medical equipment, Demographic and socioeconomic statistics, Neglected tropical diseases, International Health Regulations (2005) monitoring framework, Insecticide resistance, Oral health, Universal Health Coverage, Global Observatory for eHealth (GOe), RSUD: GOVERNANCE, POLICY AND FINANCING : PREVENTION, RSUD: GOVERNANCE, POLICY AND FINANCING: TREATMENT, RSUD: GOVERNANCE, POLICY AND FINANCING: FINANCING, RSUD: SERVICE ORGANIZATION AND DELIVERY: TREATMENT SECTORS AND PROVIDERS, RSUD: SERVICE ORGANIZATION AND DELIVERY: TREATMENT CAPACITY AND TREATMENT COVERAGE, RSUD: SERVICE ORGANIZATION AND DELIVERY: PHARMACOLOGICAL TREATMENT, RSUD: SERVICE ORGANIZATION AND DELIVERY: SCREENING AND BRIEF INTERVENTIONS, RSUD: SERVICE ORGANIZATION AND DELIVERY: PREVENTION PROGRAMS AND PROVIDERS, RSUD: SERVICE ORGANIZATION AND DELIVERY: SPECIAL PROGRAMMES AND SERVICES, RSUD: HUMAN RESOURCES, RSUD: INFORMATION SYSTEMS, RSUD: YOUTH, FINANCIAL PROTECTION, AMR GLASS Coordination, AMR GLASS Surveillance, AMR GLASS Quality assurance, Noncommunicable diseases and mental health, Health workforce, Neglected Tropical Diseases, AMR GASP, ICD For links to individual indicator metadata, see resource descriptions.
  • 50+ Downloads
    Updated March 20, 2020 | Dataset date: Jan 1, 1990-Dec 31, 1990
    This dataset updates: Every year
    Contains data from the DHS data portal. There is also a dataset containing Sudan - National Demographic and Health Data on HDX. The DHS Program Application Programming Interface (API) provides software developers access to aggregated indicator data from The Demographic and Health Surveys (DHS) Program. The API can be used to create various applications to help analyze, visualize, explore and disseminate data on population, health, HIV, and nutrition from more than 90 countries.
  • 100+ Downloads
    Updated March 20, 2020 | Dataset date: Jan 1, 1990-Dec 31, 1990
    This dataset updates: Every year
    Contains data from the DHS data portal. There is also a dataset containing Sudan - Subnational Demographic and Health Data on HDX. The DHS Program Application Programming Interface (API) provides software developers access to aggregated indicator data from The Demographic and Health Surveys (DHS) Program. The API can be used to create various applications to help analyze, visualize, explore and disseminate data on population, health, HIV, and nutrition from more than 90 countries.
  • 3100+ Downloads
    Updated March 20, 2020 | Dataset date: Mar 20, 2020
    This dataset updates: Every year
    Sudan administrative level 0 (country), 1 (state), and 2 (district) boundary files Vetting and live service provision by Information Technology Outreach Services (ITOS) with funding from USAID.
  • 1500+ Downloads
    Updated March 20, 2020 | Dataset date: Jan 1, 2017-Feb 29, 2020
    This dataset updates: Every month
    This page provides the data published in the Education in Danger Monthly News Brief. All data contains incidents identified in open sources. Categorized by country and with link to the relevant Monthly News Brief (where possible).
  • 100+ Downloads
    Updated March 19, 2020 | Dataset date: Oct 1, 2018-Aug 31, 2019
    This dataset updates: Every six months
    An estimated 5.8 million people (14% of the total population) are experiencing Crisis or worse levels of food insecurity (IPC Phase 3 and above) and are in need urgent action. This figure is the highest on record since the introduction of the IPC analysis in Sudan. Around 1 million individuals are facing Emergency levels of acute food insecurity (IPC Phase 4) and around 4.8 million individuals are in Crisis (IPC Phase 3), while nearly 11.8 million are estimated to be in Stress Phase (IPC Phase 2). Overall, 162 localities from 17 states have been classified out of the 18 Sudan States. For more visit: ipcinfo.org
  • 1700+ Downloads
    Updated March 17, 2020 | Dataset date: Jan 1, 2019-Feb 29, 2020
    This dataset updates: Every month
    This page provides the data published in the Attacks on Health Care Monthly News Brief. For data supporting the Safeguarding Health in Conflict Coalition (SHCC), please see: https://data.humdata.org/dataset/shcchealthcare-dataset These datasets covers events where health workers were killed, kidnapped or arrested (KKA) and incidents where health facilities were damaged or destroyed by a perpetrator including state and non-state actors, criminals, individuals, students and other staff members in 2019 and in 2020 to date. All data contains incidents identified in open sources. Categorized by country and with links to relevant Monthly News Brief.
  • 10+ Downloads
    Updated March 16, 2020 | Dataset date: Dec 31, 2018
    This dataset updates: As needed
    Methodology The survey used the Simple Spatial Survey Method (S3M), an area-based sampling methodology that uses settlement locations for sample selection. The survey was designed to be spatially representative of the whole country its smaller administrative units up to the locality level with the exception of few inaccessible areas . An even distribution of primary sampling units (PSUs) (i.e., villages/city blocks) was selected from across the country. This approach was used as it is most suited to assessing indicators over wide areas to detect and map heterogeneity of indicators which is the primary objectives of this national survey (Gilbert 1987; Elliot et al. 2000; Pfeiffer 2008). PSUs (i.e. villages/city blocks) were selected based on their proximity to centroids of a hexagonal grid laid over the entire country. The resulting sample is a triangular irregular network (Pfeiffer 2008; E. H. Isaaks and Srivastava 1989). A variable density sampling approach (E. H. Isaaks and Srivastava 1989) was used to achieve a sample that draws a minimum number of PSUs from localities and from urban areas so that they can provide estimates for each of these areas with useful precision. A sample of up to n = 32 mother and child pairs in m = 3027 PSUs was taken (see Figure 2.1). Across Sudan, a total of 93,882 households and 145,002 children below 5 years of age were surveyed. Preparations, data collection and analysis: Planning of the S3M II survey and in particular, the timeframe of activities, was based on the previous experience of undertaking S3M-I but also influenced the inputs of stakeholders at federal and state level, particularly members of the S3M-II technical committee at federal level, which included WHO, WFP, the Ministry of Education (MOE), the Ministry of Security and Social Welfare (MOSSW) and the Ministry of Agriculture (food security directorate), besides the Ministry of Health and UNICEF. FMoH and UNICEF, through the S3M II technical committee, regularly engaged with key stakeholders (one to two times per week during the planning phase) and ensured their involvement in the analysis stage. All technical committee members were invited to participate in the data analysis workshops. Other stakeholders - like the Central Bureau of Statistics (CBS) were consulted and informed of the progress achieved during each of the key stages (preparation, data collection and data analysis) while stakeholders such as donors were informed of progress. In addition, in every state, state level technical committees were formed and functioned to support the planning, data collection and analysis processes. The Ethical approval request was prepared by the FMOH and submitted to the ethics committee at the research department at the FMOH. Ethical approval was granted for both S3M-II and the nested micronutrients survey from FMOH. All other relevant approvals related to undertaking the survey were obtained including visas for international consultants supporting the survey, travel permits etc. Detailed maps for all states were obtained through a successful partnership between UNICEF, FMOH and CBS. A joint workshop was undertaken in May 2018 followed by field visits in June 2018 to verify all coordinates was conducted (workshop hosted at the CBS). This was followed with a joint field visits to obtain and physically collect missing coordinates. Through UNICEF Valid International with Brixton Health were contracted and the organisations worked closely with FMOH and UNICEF throughout the survey as planned. It should be noted that the individuals included in the institutional contract were the experts who developed and later refined the S3M methodology as well as provided support to the wider Sudan team with the undertaking of the S3M-I survey in 2013. Initial list of the indicators to be included in the survey was developed through wide consultation with various sectors and stakeholders including government line ministries (MoH, MoE, MSSW, MoA) and UN agencies (UNICEF, WHO and WFP) through the S3M technical committee. The proposed list was further refined and revised by an external firm (Valid international organization) who also provided technical support throughout the survey. 226 indicators were collected and reported (see annex 1 for details). Survey leads from UNICEF and MoH were identified and they further identified 9 UNICEF, 20 FMoH and 18 SMoH staff to supervise data collection and management. During Gezira pilot, the supervisors were trained to serve as data collectors to sharpen their skills to lead the data collection process in their respective states.. As a result, there were nine UNICEF, 20 Federal and 18 state level supervisors in addition to four supervisors from WHO who participated to oversee the collection of the micronutrient related data, as did their counterparts from the FMOH. Finally, a third-party ICT company was contracted by the FMOH to develop data collection digital tools and to provide ICT technical support and troubleshooting with regard to tablets and software issues, including presence of one ICT person in each state throughout the data collection. Sampling was carried out from 11 to 23 July 2018 by UNICEF and Ministry of Health staff in accordance with the S3M sampling methodology. This was based on the mapping of settlements across the entire country in villages and city blocks, carried out just prior to this (in 2.3.3 above), resulting in the assignment of correct GPS coordinates for more than 25,000 villages across the country. Based on the mapping of settlements, distribution of primary sampling units was selected for each locality. This was done based on random sample selection using a sampling software designed to undertake S3M variable density sampling. The approach and selection were approved for their rigor and appropriateness by the external technical experts from Valid International. From the selected villages, consultations with state authorities including State Ministries of Health (SMOH), Humanitarian Aid Commission (HAC) and the National Intelligence and Security Service (NISS) were held to ensure the accessibility and security of villages for the survey teams and in the case of inaccessible villages, a replacement was made using the same sampling software. Further selection of households was done during the actual survey data collection; under the oversight of the external technical experts. Master training was carried-out in Gezira state (pilot state) in July-August 2018 to test tools including digital data collection tools, laboratory testing for micronutrients indicators and logistics and to train survey supervisors (through a Training of Trainers). Upon the identification of staff, all supervisors including the nine UNICEF supervisors, the four WHO supervisors, the 18 state supervisors and the 20 FMOH supervisors (including nine from Gezira state) received training from July 16 to July 25 on the following topics:  S3M-II methodology.  S3M-II questionnaire.  Digital data collection tools (tablets).  Micronutrients samples collection and storage.  TORs of all personnel and groups.  Anthropometric measurements standardisation.  S3M-II monitoring tools.  S3M-II logistic, data collection plans and quality assurance.  Local calendar.  S3M-II sampling including urban sampling. In addition, 18 state nutrition directors received basic training on the S3M-II methodology, indicators, and the roles and responsibilities for committees involved. Further training for the supervisors for the micronutrient survey were done separately. This was followed by data collection in Gezira state which was carried-out by supervisors. Subsequent state level trainings were conducted prior to data collection for each state. Data from phase one states (North Darfur, East Darfur, West Kordofan, River Nile, Sennar, South Darfur, North Kordofan, Khartoum and Northern states) was collected in October 2018. Data from phase II states (White Nile, Kassala, Blue Nile, Central Darfur and West Darfur, Red Sea, South Kordofan and Gedaref states) was collected from November 2019 to January 2019. Close monitoring, supportive supervision and capacity-building to the Ministry of Health staff continued throughout the first phase. Technical assistance was provided from UNICEF S3M-II technical staff and Valid International throughout data collection.
  • Updated March 16, 2020 | Dataset date: Sep 30, 2019
    This dataset updates: As needed
    This data-set presents the US$ value of annual imports of medicines from 2013 published by the Central Bank of Sudan on a quarterly basis on its website www.cbos.gov.sd
  • 20+ Downloads
    Updated March 16, 2020 | Dataset date: Sep 30, 2019
    This dataset updates: As needed
    Rainfall distribution in Sudan for a 2010-2019. The data-set was created using observed data from the Sudan Meteorological Authority. All measurements in millimeters.
  • 1400+ Downloads
    Updated March 14, 2020 | Dataset date: Jan 1, 2019-Feb 29, 2020
    This dataset updates: Every month
    This dataset includes incidents affecting the affecting the protection of IDPs and refugees. The data contains incidents identified in open sources. Categorized by country and with links to relevant Monthly News Brief.
  • 4600+ Downloads
    Updated March 12, 2020 | Dataset date: Jan 1, 2015-Feb 29, 2020
    This dataset updates: Every month
    This dataset contains agency- and publicly-reported data for events in which an aid worker was killed, kidnapped, or arrested. Categorized by country.
  • 10+ Downloads
    Updated March 12, 2020 | Dataset date: Dec 31, 2019
    This dataset updates: Every year
    The number of infectious disease outbreaks as reported by Sudan’s Ministry of Health in 2019. Outbreaks reported include Cholera, Dengue Fever, Diphtheria, Rift Valley Fever and Chikugunya.
  • 90+ Downloads
    Updated March 10, 2020 | Dataset date: Mar 23, 2015
    This dataset updates: Never
    The INFORM Greater Horn of Africa model is part of an initiative of Intergovernmental Authority on Development (IGAD) and OCHA to improve IGAD’s ability to analyse, visualise and disseminate information to support the prevention, preparedness and response to humanitarian crises in the region. The model will be updated regularly to support regional coordination and prioritise humanitarian, development, risk management and resilience investments.